1. Impact of the New Cohesion Policy 2014-2020 Workshop DG JRC/DG REGIO
Assessment with the Land Use Modelling Platform (LUMP)
State of the work
Workshop DG JRC/DG REGIO
24 – June , Ispra, Italy
Land Use Modelling Group
INTESA Action / Sustainability Assessment Unit / Institute of Environment and Sustainability
EC / DG JRC

2. Part I: Scenario construction
AGENDA
Part I: Scenario construction
Introduction: the reference scenario and the policy scenario(s)
The Reference Scenario. Main results achieved.
Towards the Policy Scenario(s)
Integration with Rhomolo. Preliminary results.
The population allocation module. Designing two scenarios of urban development.
Integrating the thematic investments in the simulations.

3. Part II: Ecosystem services and indicators
AGENDA
Part II: Ecosystem services and indicators
Introduction: Ecosystem services
Recreational potential and air quality
Water quality

4. Reference and Policy scenarios (in a nutshell)
Population projections
Agriculture &
Forestry
Economy
(GEM-E3)
TEN-T
Legislation
Reference Scenario (RS0)
No implementation of TEN-T
Branch: Reference Scenario (RS1)
Economy
(Rhomolo)
Implemen-tation of the TEN-T
Implementation of the thematic priorities
Policy Scenario
Comparison of scenarios at European level
Indicators on land use, ecosystem services and urban/rural systems
Branch: “BAU urban development” (PS1)
Branch: “Compact urban deve-lopment” (PS2)

5. State of the work: where are we?
The “Reference Scenario” is ready;
The specific Reference Scenario branch for DG Regio (no implementation of TEN-T) is being generated as we speak;
The Policy Scenario is not ready yet, but there is progress on several preparatory steps:
The integration between Rhomolo-LUMP has been worked-out;
The dynamic population allocation module is working (major innovation in Land Use Modelling);
Work on integrating several thematic priorities has progressed.
Indicators to assess Ecosystem Services are being developed in parallel.

6. Coming up next…
The Reference Scenario. Main results achieved.

7. Economic forecast (baseline) Economic forecast (Rhomolo)
Integration with Rhomolo
The protocol to integrate Rhomolo in LUMP was defined in the few last weeks in interaction with REMO-IPTS-Seville;
It was necessary to develop this protocol because Rhomolo is not a forecasting model.
Economic forecast (baseline)
Real GVA
Economic forecast (Rhomolo)
Base run (1)
(...)
(2) / (1)
Policy factor
Rhomolo’s simulations
Simulation run (2)

8. Economic forecast (baseline) Economic forecast (Rhomolo)
Integration with Rhomolo
Sectorial GVA forecasts in real terms are then ‘transformed’ into industrial and commercial land use demand using the validated ‘land use intensity approach’:
Land Use Intensity approach
Economic forecast (baseline)
Industrial & Comm. land use demand
Land allocation
(EUCS100m)
Land Use Intensity approach
Economic forecast (Rhomolo)
Industrial & Comm. land use demand

9. Integration with Rhomolo
While the final simulations from Rhomolo are not ready, we ran some tests on currently available simulations.
Baseline: Sectorial GVA growth generated by linear trend of observed growth rates (observations );
Policy: ‘TFP’ policy alternative:
The main assumption of the EU policy alternative is that the European Structural and Cohesion Funds raise the capacity of the regions for technical progress, catching up with the more advanced ones, taking into account the funding in the areas of research, technological development and innovation.

10. Approach “M3” (regional-specific land use intensities)
Industrial and commercial land use growth: 23% - 25%
Difference between baseline and policy: 1,6%

11. Approach “M5” (regional and sector-specific land use intensities)
Industrial and commercial land use growth: 11% - 14%
Difference between baseline and policy: 2,3%

12. Policy effect on
ICS land use demand

13. The population allocation module
New allocation core of LUMP for population and urban areas;
Dynamically allocates inhabitants (given population projections) within each modelling region (NUTS) with a resolution of 100 m;
Regional population projections
Future urban land use
Projected pixel population
Threshold rules
Indicators
Allocation mechanism
Potentially refined indicators

14. Kj,t+1 = ( Populationt+1 - Populationt ) + (Populationt * u)
The population allocation module
Allocation workflow
Regional population projections (Qj,t+1)
Regional internal migrations (u);
People to allocate in t+1in NUTS2 region j (Kj,t+1):
Kj,t+1 = ( Populationt+1 - Populationt ) + (Populationt * u)

15. The population allocation module
Allocation workflow
Define the local (pixel i) suitabilities to allocate people (population potential P):
Pi,j,t+1 = f ( Accessibility, Neighboring Population, Distance to roads, Slope, Housing Supply ) k

16. Qi,t+1 = [ Kj,t+1 * ( Pi,j,t+1 / Σj Pi,j,t+1 ) ] + [Qi,t * (1-u)]
The population allocation module
Allocation workflow
Allocate people in pixels:
Qi,t+1 = [ Kj,t+1 * ( Pi,j,t+1 / Σj Pi,j,t+1 ) ] + [Qi,t * (1-u)]
Pixel’s proportion of total suitability
People allocated at pixel level
People to allocate in each region
People that do not migrate internally from t to t+1

17. The population allocation module
Allocation workflow
Iterative procedure to allocate discrete numbers of people and check for spatial restrictions (pixel caps);
Force conversions to urban or abandoned urban according to thresholds.
Proceed with the spatial allocation of the other land uses.
Change in cell’s population density
Decreases below T1 = 2
Remains between T1 and T2
Increases beyond T2 = 6
Land use is not urban
Remains allocated land use
Becomes urban
Land use is urban
Becomes urban abandoned
Remains urban

18. The population allocation module
Direct inputs / parameters
Item
Notes
Notation
Base population distribution 2006
Disaggregated from finest geometrical source zones availabe. Qi
Demographic projections
NUTS2 level. Source: Eurostat Qj
Rate of inner regional migratons
Arbitrarily defined. Flat parameter for all regions. u

19. The population allocation module
Statistically calibrated suitability factors
Item
Notes
Notation
Potential accessibility
Dynamic in time.
Takes into account the major programmed changes in the network (provided by Transtools) as well as other smaller investments in road infrastructure (investments allocated through a modelling procedure that takes into account modelled traffic flows). -

20. The population allocation module
Statistically calibrated suitability factors
Item
Notes
Notation
Neighborhood population
Effect of neighboring population. -
Distance to roads
Based on current network, as given by TeleAtlas.
Land uses
Capacity of land uses to support the location of new houses / residents.
Slope
Effect of slope on housing construction.

21. The population allocation module
Other allocation factors
Item
Notes
Notation
Housing supply
Accounts for the inelastic supply of housing at the scale of the pixel. Housing supply is the same as of , and it is updated every 10 years. Can be used for scenario configuration. S
Power parameter
It is optimized to fit initial population distribution (commonly ~ 1.5). Reflects the possibility that housing preferences are not linear to suitability.
Ultimately can be used for scenario configuration. Strongly affects concentration / dispersal of population. k

22. The population allocation module
Conversion rules
Item
Notes
Notation
Conversion to urban
Threshold 1 >= 6 inhab T2
Conversion to abandoned urban
Threshold 2 <= 2 inhab T1
Spatial restrictions to the allocation of people
Item
Notes
Notation
Moderate restriction
N2K; CDDA V - VI. Population outside urban areas cannot grow over 6 inhab pixel-wise. -
High restriction
N2K; CDDA I - IV. Population outside urban areas t1 <= t0.

23. The population allocation module
Policy preferences affecting population allocation (locspecs’ layers)
Item
Notes
Notation
Investment in airports
Valid for both policy scenarios.
Presumably increase attractiveness to residents. -
Investment in urban multimodal transport
Investment in culture and rural/urban regeneration

24. Coming up next…
Policy alternatives: compact and disperse urban development.
Investments in road network.